Fuzzy Logic von Enric Trillas | An Introductory Course for Engineering Students | ISBN 9783319386430

Fuzzy Logic

An Introductory Course for Engineering Students

von Enric Trillas und Luka Eciolaza
Mitwirkende
Autor / AutorinEnric Trillas
Autor / AutorinLuka Eciolaza
Buchcover Fuzzy Logic | Enric Trillas | EAN 9783319386430 | ISBN 3-319-38643-3 | ISBN 978-3-319-38643-0

“It provides a nice and quick introduction to all these concepts in a very easy and understandable way. … the book is totally adequate for a basic introductory course on fuzzy logic (especially for engineering students), but also has the advantage of being ideal as a self-learning book for those who may be tangentially interested in the field.” (Joan Torrens, Mathematical Reviews, July, 2018)


“The book is slim: it compresses all the key concepts of fuzzy logic in about 200 pages. … the book would be well suited for introductory courses in other disciplines including computer science. … the approach taken by the authors to explain fuzzy logic makes me strongly recommend it for basic undergraduate and graduate courses on fuzzy logic or soft computing.” (Corrado Mencar, Computing Reviews, November, 2015)

Fuzzy Logic

An Introductory Course for Engineering Students

von Enric Trillas und Luka Eciolaza
Mitwirkende
Autor / AutorinEnric Trillas
Autor / AutorinLuka Eciolaza
This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introductory textbook on fuzzy logic, presenting theory together with examples and not always following the typical mathematical style of theorem-corollaries. Primarily intended to support engineers during their university studies, and to spark their curiosity about fuzzy logic and its applications, the book is also suitable for self-study, providing a valuable resource for engineers and professionals who deal with imprecision and non-random uncertainty in real-world applications.